New Records of California Serogroup Virus in <i>Aedes</i> Mosquitoes and First Detection in Simulioidae Flies from Northern Canada and Alaska
Bibliographic record
Abstract
Abstract An expected consequence of climate warming is an expansion of the geographic distribution of biting insects and associated arthropod-borne diseases (arboviruses). Emerging and reemerging arboviruses that can affect human health are likely to pose significant consequences for Northern communities where access to health resources is limited. In the North American Arctic, little is known about arboviruses. Thus, in 2019, we sampled biting insects in Nunavik (Kuujjuaq), Nunavut (Igloolik, Karrak Lake and Cambridge Bay), Northwest Territories (Igloolik and Yellowknife) and Alaska (Fairbanks). The main objective was to detect the presence of California serogroup viruses (CSGv) – a widespread group of arboviruses across North America and that is known to cause a wide range of symptoms, ranging from mild febrile illness to fatal encephalitis. Biting insects were captured twice daily for a 7-day period in mid-summer, using a standardized protocol consisting of 100 figure-eight movements of a sweep net. Captured specimens were separated by genus (mosquitoes) or by superfamily (other insects), and then grouped into pools of 75 by geographical locations. In total, 5079 Aedes mosquitoes and 1014 Simulioidae flies were caught. We report the detection of CSGv RNA in mosquitoes captured in Nunavut (Karrak Lake) and Nunavik (Kuujjuaq). We also report, for the first time in North America, the presence of CSGv RNA in Simulioidae flies. These results highlight the potential of biting insects for tracking any future emergence of arboviruses in the North, thereby providing key information for public health in Northern communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".